/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 *    EntropyBasedSplitCrit.java
 *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers.trees.j48;

/**
 * "Abstract" class for computing splitting criteria based on the entropy of a
 * class distribution.
 * 
 * @author Eibe Frank (eibe@cs.waikato.ac.nz)
 * @version $Revision: 1.8 $
 */
public abstract class EntropyBasedSplitCrit extends SplitCriterion {

	/** for serialization */
	private static final long serialVersionUID = -2618691439791653056L;

	/** The log of 2. */
	protected static double log2 = Math.log(2);

	/**
	 * Help method for computing entropy.
	 */
	public final double logFunc(double num) {

		// Constant hard coded for efficiency reasons
		if (num < 1e-6)
			return 0;
		else
			return num * Math.log(num) / log2;
	}

	/**
	 * Computes entropy of distribution before splitting.
	 */
	public final double oldEnt(Distribution bags) {

		double returnValue = 0;
		int j;

		for (j = 0; j < bags.numClasses(); j++)
			returnValue = returnValue + logFunc(bags.perClass(j));
		return logFunc(bags.total()) - returnValue;
	}

	/**
	 * Computes entropy of distribution after splitting.
	 */
	public final double newEnt(Distribution bags) {

		double returnValue = 0;
		int i, j;

		for (i = 0; i < bags.numBags(); i++) {
			for (j = 0; j < bags.numClasses(); j++)
				returnValue = returnValue + logFunc(bags.perClassPerBag(i, j));
			returnValue = returnValue - logFunc(bags.perBag(i));
		}
		return -returnValue;
	}

	/**
	 * Computes entropy after splitting without considering the class values.
	 */
	public final double splitEnt(Distribution bags) {

		double returnValue = 0;
		int i;

		for (i = 0; i < bags.numBags(); i++)
			returnValue = returnValue + logFunc(bags.perBag(i));
		return logFunc(bags.total()) - returnValue;
	}
}
